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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Tebbs, Emma J.; Rowland, Clare S.; Smart, Simon M.; Maskell, Lindsay C.; +1 Authors

    This paper presents an alternative approach for high spatial resolution vegetation productivity mapping at a regional scale, using a combination of Normalised Difference Vegetation Index (NDVI) imagery and widely distributed ground-based Above-ground Net Primary Production (ANPP) estimates. Our method searches through all available single-date NDVI imagery to identify the images which give the best NDVI–ANPP relationship. The derived relationships are then used to predict ANPP values outside of field survey plots. This approach enables the use of the high spatial resolution (30 m) Landsat 8 sensor, despite its low revisit frequency that is further reduced by cloud cover. This is one of few studies to investigate the NDVI–ANPP relationship across a wide range of temperate habitats and strong relationships were observed (R2 = 0.706), which increased when only grasslands were considered (R2 = 0.833). The strongest NDVI–ANPP relationships occurred during the spring “green-up” period. A reserved subset of 20% of ground-based ANPP estimates was used for validation and results showed that our method was able to estimate ANPP with a RMSE of 15–21%. This work is important because we demonstrate a general methodological framework for mapping of ANPP from local to regional scales, with the potential to be applied to any temperate ecosystems with a pronounced green up period. Our approach allows spatial extrapolation outside of field survey plots to produce a continuous surface product, useful for capturing spatial patterns and representing small-scale heterogeneity, and well-suited for modelling applications. The data requirements for implementing this approach are also discussed.

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    Article . 2017
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    Article . 2017
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    Authors: Annecchino, LA; Morris, AR; Copeland, CS; Agabi, OE; +2 Authors

    Summary Whole-cell patch-clamp electrophysiological recording is a powerful technique for studying cellular function. While in vivo patch-clamp recording has recently benefited from automation, it is normally performed “blind,” meaning that throughput for sampling some genetically or morphologically defined cell types is unacceptably low. One solution to this problem is to use two-photon microscopy to target fluorescently labeled neurons. Combining this with robotic automation is difficult, however, as micropipette penetration induces tissue deformation, moving target cells from their initial location. Here we describe a platform for automated two-photon targeted patch-clamp recording, which solves this problem by making use of a closed loop visual servo algorithm. Our system keeps the target cell in focus while iteratively adjusting the pipette approach trajectory to compensate for tissue motion. We demonstrate platform validation with patch-clamp recordings from a variety of cells in the mouse neocortex and cerebellum. Highlights • A system for robotically targeted neurophysiological recording is demonstrated • The platform keeps the target in focus and corrects the electrode trajectory • The system compensates for micropipette-induced tissue deformations • Targeted recordings were obtained from several fluorescently labeled cells in vivo Annecchino et al. describe a platform for robotic two-photon targeted patch-clamp recording and demonstrate its functionality by recording from a variety of fluorescently targeted cell types in mouse neocortex and cerebellum.

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    Authors: Dupraz C.; Wolz K. J.; Lecomte I.; Talbot G.; +15 Authors

    International audience; Agroforestry, the intentional integration of trees with crops and/or livestock, can lead to multiple economic and ecological benefits compared to trees and crops/livestock grown separately. Field experimentation has been the primary approach to understanding the tree-crop interactions inherent in agroforestry. However, the number of field experiments has been limited by slow tree maturation and difficulty in obtaining consistent funding. Models have the potential to overcome these hurdles and rapidly advance understanding of agroforestry systems. Hi-sAFe is a mechanistic, biophysical model designed to explore the interactions within agroforestry systems that mix trees with crops. The model couples the pre-existing STICS crop model to a new tree model that includes several plasticity mechanisms responsive to tree-tree and tree-crop competition for light, water, and nitrogen. Monoculture crop and tree systems can also be simulated, enabling calculation of the land equivalent ratio. The model's 3D and spatially explicit form is key for accurately representing many competition and facilitation processes. Hi-sAFe is a novel tool for exploring agroforestry designs (e.g., tree spacing, crop type, tree row orientation), management strategies (e.g., thinning, branch pruning, root pruning, fertilization, irrigation), and responses to environmental variation (e.g., latitude, climate change, soil depth, soil structure and fertility, fluctuating water table). By improving our understanding of the complex interactions within agroforestry systems, Hi-sAFe can ultimately facilitate adoption of agroforestry as a sustainable land-use practice.

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    ProdInra
    Article . 2019
    License: CC BY
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    Horizon / Pleins textes
    Other literature type . 2019
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    Sustainability
    Article . 2019
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    Article . 2019
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    Authors: Peng, T.; Jermyn, I. H.; Prinet, V.; Zerubia, J.;

    International audience; This paper addresses the segmentation from an image of entities that have the form of a `network', \ie the region in the image corresponding to the entity is composed of branches joining together at junctions, \eg road or vascular networks. We present new phase field higher-order active contour (HOAC) prior models for network regions, and apply them to the segmentation of road networks from very high resolution satellite images. This is a hard problem for two reasons. First, the images are complex, with much `noise' in the road region due to cars, road markings, etc., while the background is very varied, containing many features that are locally similar to roads. Second, network regions are complex to model, because they may have arbitrary topology. In particular, we address a limitation of a previous model in which network branch width was constrained to be similar to maximum network branch radius of curvature, thereby providing a poor model of networks with straight narrow branches or highly curved, wide branches. We solve this problem by introducing first an additional nonlinear nonlocal HOAC term, and then an additional linear nonlocal HOAC term to improve the computational speed. Both terms allow separate control of branch width and branch curvature, and furnish better prolongation for the same width, but the linear term has several advantages: it is more efficient, and it is able to model multiple widths simultaneously. To cope with the difficulty of parameter selection for these models, we perform a stability analysis of a long bar with a given width, and hence show how to choose the parameters of the energy functions. After adding a likelihood energy, we use both models to extract the road network quasi-automatically from pieces of a QuickBird image, and compare the results to other models in the literature. The state-of-the-art results obtained demonstrate the superiority of our new models, the importance of strong prior knowledge in general, and of the new terms in particular.

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    Authors: Taylor, Joel; Gibson, Laura Kate;

    The democratisation of heritage through digital access is a well-documented aspiration. It has included innovative ways to manage interpretation, express heritage values, and create experiences through the ‘decoding’ of heritage. This decoding of heritage becomes democratised, more polyvocal than didactic exhibitions, and less dependent on experts. However, the decision of what ‘heritage’ is and what is commissioned for digitisation (the encoding) is not necessarily a part of this democratisation. This paper will consider how digitisation reinforces the Authorised Heritage Discourse through the lens of Stephen Lukes’ three (increasingly subtle) dimensions of power: conflict resolution, control of expression and shaping of preferences. All three dimensions have an impact on how public values are represented in heritage contexts, but the introduction of digitisation requires more resources, expertise and training within established professional discourse. Social media may have a positive impact on the first two dimensions, but can reinforce hegemony. Alternatives are subject to epistemic populism. The role of digitisation and social media in the democratisation of heritage needs to be better understood. Questions regarding the nature and process of digital interaction, in terms of whose heritage is accessible, affect the very issues of democratisation digitisation appears to promote.

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    Authors: Anderson, Sheila; Blanke, Tobias;

    In this paper the authors investigate the importance of research infrastructures for arts and humanities research. They seek to outline the development of a digital research infrastructure localized in the science and engineering domain and framed within the concept of e-Science. The authors define the primary characteristics of e-Science as big data and big structures such as the grid and high performance computing. They will attempt to demonstrate the transfer of the e-Science paradigm to the humanities and to assess what worked and what did not. They then suggest how thinking about technology and infrastructure through and within the humanities can lead to transformation and finish with a suggestion that the future for humanities research infrastructures is best framed around the emerging idea of a humanities specific digital ecosystem. Historical Social Research Vol. 37, No. 3 (2012)

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    https://doi.org/10.12759/hsr.3...
    Article . 2012
    License: CC BY
    Data sources: Datacite
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      https://doi.org/10.12759/hsr.3...
      Article . 2012
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  • Authors: Hoegstrom, E.; Trofaier, A.M.; Gouttevin, I.; Bartsch, A.;

    [Departement_IRSTEA]Eaux [TR1_IRSTEA]ARCEAU; International audience; Knowledge of surface hydrology is essential for many applications, including studies that aim to understand permafrost response to changing climate and the associated feedback mechanisms. Advanced remote sensing techniques make it possible to retrieve a range of land-surface variables, including radar retrieved soil moisture (SSM). It has been pointed out before that soil moisture retrieval from satellite data can be challenging at high latitudes, which correspond to remote areas where ground data are scarce and the applicability of satellite data of this type is essential. This study investigates backscatter variability other than associated with changing soil moisture in order to examine the possible impact on soil moisture retrieval. It focuses on issues specific to SSM retrieval in the Arctic, notably variations related to tundra lakes. ENVISAT Advanced Synthetic Aperture Radar (ASAR) Wide Swath (WS, 120 m) data are used to understand and quantify impacts on Metop (AAdvanced Scatterometer (ASCAT, 25 km) soil moisture retrieval during the snow free period. Sites of interest are chosen according to ASAR WS availability, high or low agreement between output from the land surface model ORCHIDEE and ASCAT derived SSM. Backscatter variations are analyzed with respect to the ASCAT footprint area. It can be shown that the low model agreement is related to water fraction in most cases.No difference could be detected between periods with floating ice (in snow off situation) and ice free periods at the chosen sites. The mean footprint backscatter is however impacted by partial short term surface roughness change. The water fraction correlates with backscatter deviations (relative to a smooth water surface reference image) within the ASCAT footprint areas . Backscatter deviations of up to 5 dB can occur in areas with less than 50% water fraction and an assumed soil moisture related range (sensitivity) of 7 dB in the ASCAT data. The sensitivity is also positively correlated with water fraction in regions with low land-surface model agreement (R = 0.68). A precise quantification of the impact on soil moisture retrieval would, however, need to consider actual soil moisture changes and sensor differences. The study demonstrates that the usage of higher spatial resolution data than currently available for SSM is required in lowland permafrost environments.; La connaissance de l'hydrologie de surface est essentielle mais difficile aux hautes latitudes du fait de la rareté des observations. Les observations satellites offrent le moyen d'y pallier, mais encore faut-il s'assurer de la validité de ces approches dans ces régions. Par l'intermédiaire de deux jeux de données satellite de résolutions différentes, on étudie ici la sensibilité du signal de micro-ondes actives rétrodiffusées à des facteurs autres que l'humidité superficielle des sols.Les zones d'étude ont été ciblées pour correspondre à des régions où les modèles hydrologiques divergent des observations. Dans la plupart de ces zones, l'utilisation d'un produit satellite à fine résolution met en évidence l'impact des lacs sur le signal micro-onde observé, et utilisé pour inférer l'humidité superficielle dans les produits satellites. Il est donc nécessaire d'apporter des corrections aux produits satellitaires dans les régions où la forte concentration en étendues d'eau libre et l'occurrence de vents violents en limitent la validité pour l'hydrologie de surface.

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    Authors: Latruffe, Laure; Mann, Stefan;

    In this paper we suggest that low labour availability on part-time farms may limit part-time farmers’ choice of production enterprises, and as a consequence those farmers may be forced to engage in less profitable enterprises. This proposition is illustrated by a conceptual framework based on the assumption that products with high returns to labour are labour intensive. An empirical analysis for the period 1996-2004 based on aggregated yearly data from the Swiss Farm Accountancy Data Network (FADN) did not fully confirm the proposition. This may suggest the existence of a joint determination of the choice of production enterprise and of the choice to work off the farm. In addition, our assumption that highly profitable enterprises are labour intensive may not hold for specific products or contexts. Bio-based and Applied Economics, Vol 4 No 2 (2015)

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    Authors: Martin Prchal; Antti Kause; Marc Vandeputte; David Gela; +6 Authors

    Correction(fichier annexe) : The genetics of overwintering performance in two-year old common carp and its relation to performance until market size (vol 13, e0191624, 2018); Using farmed common carp, we investigated the genetic background of the second year overwintering performance and its relation to the performance during the third growing season and at market size. The experimental stock was established by partial factorial design with a series of 4 factorial matings of 5 dams and 10 sires each. The families were reared communally and pedigree was re-constructed with 93.6% success using 12 microsatellites on 2008 offspring. Three successive recordings (second autumn, third spring, and third autumn—market size) covering two periods (second overwintering, third growing season) were included. Body weight, Fulton’s condition factor and percent muscle fat content were recorded at all times and headless carcass yield and fillet yield were recorded at market size. Specific growth rate, absolute and relative fat change and overall survival were calculated for each period. Heritability estimates were significantly different from zero and almost all traits were moderately to highly heritable (h2 = 0.36–1.00), except survival in both periods and fat change (both patterns) during overwintering (h2 = 0.12–0.15). Genetic and phenotypic correlations imply that selection against weight loss and fat loss during overwintering is expected to lead to a better winter survival, together with a positive effect on growth in the third growing season. Interestingly, higher muscle fat content was genetically correlated to lower survival in the following period (rg = -0.59; -0.53, respectively for winter and the third summer). On the other hand, higher muscle fat was also genetically linked to better slaughter yields. Moreover, selection for higher condition factor would lead to better performance during winter, growing season and at market size.

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    Authors: Mercier, Audrey; Betbeder, Julie; Rumiano, Florent; Baudry, Jacques,; +8 Authors

    Monitoring forest–agriculture mosaics is crucial for understanding landscape heterogeneity and managing biodiversity. Mapping these mosaics from remotely sensed imagery remains challenging, since ecological gradients from forested to agricultural areas make characterizing vegetation more difficult. The recent synthetic aperture radar (SAR) Sentinel-1 (S-1) and optical Sentinel-2 (S-2) time series provide a great opportunity to monitor forest–agriculture mosaics due to their high spatial and temporal resolutions. However, while a few studies have used the temporal resolution of S-2 time series alone to map land cover and land use in cropland and/or forested areas, S-1 time series have not yet been investigated alone for this purpose. The combined use of S-1 & S-2 time series has been assessed for only one or a few land cover classes. In this study, we assessed the potential of S-1 data alone, S-2 data alone, and their combined use for mapping forest–agriculture mosaics over two study areas: a temperate mountainous landscape in the Cantabrian Range (Spain) and a tropical forested landscape in Paragominas (Brazil). Satellite images were classified using an incremental procedure based on an importance rank of the input features. The classifications obtained with S-2 data alone (mean kappa index = 0.59–0.83) were more accurate than those obtained with S-1 data alone (mean kappa index = 0.28–0.72). Accuracy increased when combining S-1 and 2 data (mean kappa index = 0.55–0.85). The method enables defining the number and type of features that discriminate land cover classes in an optimal manner according to the type of landscape considered. The best configuration for the Spanish and Brazilian study areas included 5 and 10 features, respectively, for S-2 data alone and 10 and 20 features, respectively, for S-1 data alone. Short-wave infrared and VV and VH polarizations were key features of S-2 and S-1 data, respectively. In addition, the method enables defining key periods that discriminate land cover classes according to the type of images used. For example, in the Cantabrian Range, winter and summer were key for S-2 time series, while spring and winter were key for S-1 time series.

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    Remote Sensing
    Article . 2019
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    Authors: Tebbs, Emma J.; Rowland, Clare S.; Smart, Simon M.; Maskell, Lindsay C.; +1 Authors

    This paper presents an alternative approach for high spatial resolution vegetation productivity mapping at a regional scale, using a combination of Normalised Difference Vegetation Index (NDVI) imagery and widely distributed ground-based Above-ground Net Primary Production (ANPP) estimates. Our method searches through all available single-date NDVI imagery to identify the images which give the best NDVI–ANPP relationship. The derived relationships are then used to predict ANPP values outside of field survey plots. This approach enables the use of the high spatial resolution (30 m) Landsat 8 sensor, despite its low revisit frequency that is further reduced by cloud cover. This is one of few studies to investigate the NDVI–ANPP relationship across a wide range of temperate habitats and strong relationships were observed (R2 = 0.706), which increased when only grasslands were considered (R2 = 0.833). The strongest NDVI–ANPP relationships occurred during the spring “green-up” period. A reserved subset of 20% of ground-based ANPP estimates was used for validation and results showed that our method was able to estimate ANPP with a RMSE of 15–21%. This work is important because we demonstrate a general methodological framework for mapping of ANPP from local to regional scales, with the potential to be applied to any temperate ecosystems with a pronounced green up period. Our approach allows spatial extrapolation outside of field survey plots to produce a continuous surface product, useful for capturing spatial patterns and representing small-scale heterogeneity, and well-suited for modelling applications. The data requirements for implementing this approach are also discussed.

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    Authors: Annecchino, LA; Morris, AR; Copeland, CS; Agabi, OE; +2 Authors

    Summary Whole-cell patch-clamp electrophysiological recording is a powerful technique for studying cellular function. While in vivo patch-clamp recording has recently benefited from automation, it is normally performed “blind,” meaning that throughput for sampling some genetically or morphologically defined cell types is unacceptably low. One solution to this problem is to use two-photon microscopy to target fluorescently labeled neurons. Combining this with robotic automation is difficult, however, as micropipette penetration induces tissue deformation, moving target cells from their initial location. Here we describe a platform for automated two-photon targeted patch-clamp recording, which solves this problem by making use of a closed loop visual servo algorithm. Our system keeps the target cell in focus while iteratively adjusting the pipette approach trajectory to compensate for tissue motion. We demonstrate platform validation with patch-clamp recordings from a variety of cells in the mouse neocortex and cerebellum. Highlights • A system for robotically targeted neurophysiological recording is demonstrated • The platform keeps the target in focus and corrects the electrode trajectory • The system compensates for micropipette-induced tissue deformations • Targeted recordings were obtained from several fluorescently labeled cells in vivo Annecchino et al. describe a platform for robotic two-photon targeted patch-clamp recording and demonstrate its functionality by recording from a variety of fluorescently targeted cell types in mouse neocortex and cerebellum.

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    Authors: Dupraz C.; Wolz K. J.; Lecomte I.; Talbot G.; +15 Authors

    International audience; Agroforestry, the intentional integration of trees with crops and/or livestock, can lead to multiple economic and ecological benefits compared to trees and crops/livestock grown separately. Field experimentation has been the primary approach to understanding the tree-crop interactions inherent in agroforestry. However, the number of field experiments has been limited by slow tree maturation and difficulty in obtaining consistent funding. Models have the potential to overcome these hurdles and rapidly advance understanding of agroforestry systems. Hi-sAFe is a mechanistic, biophysical model designed to explore the interactions within agroforestry systems that mix trees with crops. The model couples the pre-existing STICS crop model to a new tree model that includes several plasticity mechanisms responsive to tree-tree and tree-crop competition for light, water, and nitrogen. Monoculture crop and tree systems can also be simulated, enabling calculation of the land equivalent ratio. The model's 3D and spatially explicit form is key for accurately representing many competition and facilitation processes. Hi-sAFe is a novel tool for exploring agroforestry designs (e.g., tree spacing, crop type, tree row orientation), management strategies (e.g., thinning, branch pruning, root pruning, fertilization, irrigation), and responses to environmental variation (e.g., latitude, climate change, soil depth, soil structure and fertility, fluctuating water table). By improving our understanding of the complex interactions within agroforestry systems, Hi-sAFe can ultimately facilitate adoption of agroforestry as a sustainable land-use practice.

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    Other literature type . 2019
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    Sustainability
    Article . 2019
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    Authors: Peng, T.; Jermyn, I. H.; Prinet, V.; Zerubia, J.;

    International audience; This paper addresses the segmentation from an image of entities that have the form of a `network', \ie the region in the image corresponding to the entity is composed of branches joining together at junctions, \eg road or vascular networks. We present new phase field higher-order active contour (HOAC) prior models for network regions, and apply them to the segmentation of road networks from very high resolution satellite images. This is a hard problem for two reasons. First, the images are complex, with much `noise' in the road region due to cars, road markings, etc., while the background is very varied, containing many features that are locally similar to roads. Second, network regions are complex to model, because they may have arbitrary topology. In particular, we address a limitation of a previous model in which network branch width was constrained to be similar to maximum network branch radius of curvature, thereby providing a poor model of networks with straight narrow branches or highly curved, wide branches. We solve this problem by introducing first an additional nonlinear nonlocal HOAC term, and then an additional linear nonlocal HOAC term to improve the computational speed. Both terms allow separate control of branch width and branch curvature, and furnish better prolongation for the same width, but the linear term has several advantages: it is more efficient, and it is able to model multiple widths simultaneously. To cope with the difficulty of parameter selection for these models, we perform a stability analysis of a long bar with a given width, and hence show how to choose the parameters of the energy functions. After adding a likelihood energy, we use both models to extract the road network quasi-automatically from pieces of a QuickBird image, and compare the results to other models in the literature. The state-of-the-art results obtained demonstrate the superiority of our new models, the importance of strong prior knowledge in general, and of the new terms in particular.

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    Authors: Taylor, Joel; Gibson, Laura Kate;

    The democratisation of heritage through digital access is a well-documented aspiration. It has included innovative ways to manage interpretation, express heritage values, and create experiences through the ‘decoding’ of heritage. This decoding of heritage becomes democratised, more polyvocal than didactic exhibitions, and less dependent on experts. However, the decision of what ‘heritage’ is and what is commissioned for digitisation (the encoding) is not necessarily a part of this democratisation. This paper will consider how digitisation reinforces the Authorised Heritage Discourse through the lens of Stephen Lukes’ three (increasingly subtle) dimensions of power: conflict resolution, control of expression and shaping of preferences. All three dimensions have an impact on how public values are represented in heritage contexts, but the introduction of digitisation requires more resources, expertise and training within established professional discourse. Social media may have a positive impact on the first two dimensions, but can reinforce hegemony. Alternatives are subject to epistemic populism. The role of digitisation and social media in the democratisation of heritage needs to be better understood. Questions regarding the nature and process of digital interaction, in terms of whose heritage is accessible, affect the very issues of democratisation digitisation appears to promote.

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    Authors: Anderson, Sheila; Blanke, Tobias;

    In this paper the authors investigate the importance of research infrastructures for arts and humanities research. They seek to outline the development of a digital research infrastructure localized in the science and engineering domain and framed within the concept of e-Science. The authors define the primary characteristics of e-Science as big data and big structures such as the grid and high performance computing. They will attempt to demonstrate the transfer of the e-Science paradigm to the humanities and to assess what worked and what did not. They then suggest how thinking about technology and infrastructure through and within the humanities can lead to transformation and finish with a suggestion that the future for humanities research infrastructures is best framed around the emerging idea of a humanities specific digital ecosystem. Historical Social Research Vol. 37, No. 3 (2012)

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    https://doi.org/10.12759/hsr.3...
    Article . 2012
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      https://doi.org/10.12759/hsr.3...
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  • Authors: Hoegstrom, E.; Trofaier, A.M.; Gouttevin, I.; Bartsch, A.;

    [Departement_IRSTEA]Eaux [TR1_IRSTEA]ARCEAU; International audience; Knowledge of surface hydrology is essential for many applications, including studies that aim to understand permafrost response to changing climate and the associated feedback mechanisms. Advanced remote sensing techniques make it possible to retrieve a range of land-surface variables, including radar retrieved soil moisture (SSM). It has been pointed out before that soil moisture retrieval from satellite data can be challenging at high latitudes, which correspond to remote areas where ground data are scarce and the applicability of satellite data of this type is essential. This study investigates backscatter variability other than associated with changing soil moisture in order to examine the possible impact on soil moisture retrieval. It focuses on issues specific to SSM retrieval in the Arctic, notably variations related to tundra lakes. ENVISAT Advanced Synthetic Aperture Radar (ASAR) Wide Swath (WS, 120 m) data are used to understand and quantify impacts on Metop (AAdvanced Scatterometer (ASCAT, 25 km) soil moisture retrieval during the snow free period. Sites of interest are chosen according to ASAR WS availability, high or low agreement between output from the land surface model ORCHIDEE and ASCAT derived SSM. Backscatter variations are analyzed with respect to the ASCAT footprint area. It can be shown that the low model agreement is related to water fraction in most cases.No difference could be detected between periods with floating ice (in snow off situation) and ice free periods at the chosen sites. The mean footprint backscatter is however impacted by partial short term surface roughness change. The water fraction correlates with backscatter deviations (relative to a smooth water surface reference image) within the ASCAT footprint areas . Backscatter deviations of up to 5 dB can occur in areas with less than 50% water fraction and an assumed soil moisture related range (sensitivity) of 7 dB in the ASCAT data. The sensitivity is also positively correlated with water fraction in regions with low land-surface model agreement (R = 0.68). A precise quantification of the impact on soil moisture retrieval would, however, need to consider actual soil moisture changes and sensor differences. The study demonstrates that the usage of higher spatial resolution data than currently available for SSM is required in lowland permafrost environments.; La connaissance de l'hydrologie de surface est essentielle mais difficile aux hautes latitudes du fait de la rareté des observations. Les observations satellites offrent le moyen d'y pallier, mais encore faut-il s'assurer de la validité de ces approches dans ces régions. Par l'intermédiaire de deux jeux de données satellite de résolutions différentes, on étudie ici la sensibilité du signal de micro-ondes actives rétrodiffusées à des facteurs autres que l'humidité superficielle des sols.Les zones d'étude ont été ciblées pour correspondre à des régions où les modèles hydrologiques divergent des observations. Dans la plupart de ces zones, l'utilisation d'un produit satellite à fine résolution met en évidence l'impact des lacs sur le signal micro-onde observé, et utilisé pour inférer l'humidité superficielle dans les produits satellites. Il est donc nécessaire d'apporter des corrections aux produits satellitaires dans les régions où la forte concentration en étendues d'eau libre et l'occurrence de vents violents en limitent la validité pour l'hydrologie de surface.

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    Authors: Latruffe, Laure; Mann, Stefan;

    In this paper we suggest that low labour availability on part-time farms may limit part-time farmers’ choice of production enterprises, and as a consequence those farmers may be forced to engage in less profitable enterprises. This proposition is illustrated by a conceptual framework based on the assumption that products with high returns to labour are labour intensive. An empirical analysis for the period 1996-2004 based on aggregated yearly data from the Swiss Farm Accountancy Data Network (FADN) did not fully confirm the proposition. This may suggest the existence of a joint determination of the choice of production enterprise and of the choice to work off the farm. In addition, our assumption that highly profitable enterprises are labour intensive may not hold for specific products or contexts. Bio-based and Applied Economics, Vol 4 No 2 (2015)

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    Authors: Martin Prchal; Antti Kause; Marc Vandeputte; David Gela; +6 Authors

    Correction(fichier annexe) : The genetics of overwintering performance in two-year old common carp and its relation to performance until market size (vol 13, e0191624, 2018); Using farmed common carp, we investigated the genetic background of the second year overwintering performance and its relation to the performance during the third growing season and at market size. The experimental stock was established by partial factorial design with a series of 4 factorial matings of 5 dams and 10 sires each. The families were reared communally and pedigree was re-constructed with 93.6% success using 12 microsatellites on 2008 offspring. Three successive recordings (second autumn, third spring, and third autumn—market size) covering two periods (second overwintering, third growing season) were included. Body weight, Fulton’s condition factor and percent muscle fat content were recorded at all times and headless carcass yield and fillet yield were recorded at market size. Specific growth rate, absolute and relative fat change and overall survival were calculated for each period. Heritability estimates were significantly different from zero and almost all traits were moderately to highly heritable (h2 = 0.36–1.00), except survival in both periods and fat change (both patterns) during overwintering (h2 = 0.12–0.15). Genetic and phenotypic correlations imply that selection against weight loss and fat loss during overwintering is expected to lead to a better winter survival, together with a positive effect on growth in the third growing season. Interestingly, higher muscle fat content was genetically correlated to lower survival in the following period (rg = -0.59; -0.53, respectively for winter and the third summer). On the other hand, higher muscle fat was also genetically linked to better slaughter yields. Moreover, selection for higher condition factor would lead to better performance during winter, growing season and at market size.

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    PLoS ONE
    Article . 2018
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    Authors: Mercier, Audrey; Betbeder, Julie; Rumiano, Florent; Baudry, Jacques,; +8 Authors

    Monitoring forest–agriculture mosaics is crucial for understanding landscape heterogeneity and managing biodiversity. Mapping these mosaics from remotely sensed imagery remains challenging, since ecological gradients from forested to agricultural areas make characterizing vegetation more difficult. The recent synthetic aperture radar (SAR) Sentinel-1 (S-1) and optical Sentinel-2 (S-2) time series provide a great opportunity to monitor forest–agriculture mosaics due to their high spatial and temporal resolutions. However, while a few studies have used the temporal resolution of S-2 time series alone to map land cover and land use in cropland and/or forested areas, S-1 time series have not yet been investigated alone for this purpose. The combined use of S-1 & S-2 time series has been assessed for only one or a few land cover classes. In this study, we assessed the potential of S-1 data alone, S-2 data alone, and their combined use for mapping forest–agriculture mosaics over two study areas: a temperate mountainous landscape in the Cantabrian Range (Spain) and a tropical forested landscape in Paragominas (Brazil). Satellite images were classified using an incremental procedure based on an importance rank of the input features. The classifications obtained with S-2 data alone (mean kappa index = 0.59–0.83) were more accurate than those obtained with S-1 data alone (mean kappa index = 0.28–0.72). Accuracy increased when combining S-1 and 2 data (mean kappa index = 0.55–0.85). The method enables defining the number and type of features that discriminate land cover classes in an optimal manner according to the type of landscape considered. The best configuration for the Spanish and Brazilian study areas included 5 and 10 features, respectively, for S-2 data alone and 10 and 20 features, respectively, for S-1 data alone. Short-wave infrared and VV and VH polarizations were key features of S-2 and S-1 data, respectively. In addition, the method enables defining key periods that discriminate land cover classes according to the type of images used. For example, in the Cantabrian Range, winter and summer were key for S-2 time series, while spring and winter were key for S-1 time series.

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    Remote Sensing
    Article . 2019
    Data sources: DOAJ-Articles
    DOAJ
    Article . 2019
    Data sources: DOAJ
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